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--- |
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language: tr |
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datasets: |
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- SUNLP-NER-Twitter |
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--- |
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# bert-loodos-sunlp-ner-turkish |
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## Introduction |
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[bert-loodos-sunlp-ner-turkish] is a NER model that was fine-tuned from the loodos/bert-base-turkish-cased model on the SUNLP-NER-Twitter dataset. |
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## Training data |
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The model was trained on the SUNLP-NER-Twitter dataset (5000 tweets). The dataset can be found at https://github.com/SU-NLP/SUNLP-Twitter-NER-Dataset |
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Named entity types are as follows: |
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Person, Location, Organization, Time, Money, Product, TV-Show |
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## How to use bert-loodos-sunlp-ner-turkish with HuggingFace |
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```python |
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from transformers import AutoTokenizer, AutoModelForTokenClassification |
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tokenizer = AutoTokenizer.from_pretrained("busecarik/bert-loodos-sunlp-ner-turkish") |
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model = AutoModelForTokenClassification.from_pretrained("busecarik/bert-loodos-sunlp-ner-turkish") |
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``` |
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## Model performances on SUNLP-NER-Twitter test set (metric: seqeval) |
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Precision|Recall|F1 |
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-|-|- |
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83.46|85.65|84.53 |
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Classification Report |
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Entity|Precision|Recall|F1 |
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-|-|-|- |
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LOCATION|0.82|0.71|0.76 |
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MONEY|0.92|0.76|0.83 |
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ORGANIZATION|0.82|0.87|0.85 |
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PERSON|0.91|0.91|0.91 |
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PRODUCT|0.57|0.33|0.42 |
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TIME|0.86|0.83|0.85 |
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TVSHOW|0.65|0.63|0.64 |
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